Return On Asset

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Indicator Description

Return on Asset measures overall efficiency of a company in generating profits from its total assets. It is expressed as the percentage of profits earned per dollar of Asset. A low ROA typically means that a company is asset-intensive and therefore will needs more money to continue generating revenue in the future.

Return On Asset

 = 

Net Income

Total Assets

Return on Asset or ROA shows how effective is the management of the company in generating income from utilizing all of the assets at their disposal. It is a useful ratio to evaluate the performance of different departments of a company as well as to understand management performance over time.

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Analyzing currently trending equities could be an opportunity to develop a better portfolio based on different market momentums that they can trigger. Utilizing the top trending stocks is also useful when creating a market-neutral strategy or pair trading technique involving a short or a long position in a currently trending equity.

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The classical approach to portfolio optimization is known as Modern Portfolio Theory (MPT). It involves categorizing the investment universe based on risk (standard deviation) and return, and then choosing the mix of investments that achieves the desired risk-versus-return tradeoff. Portfolio optimization can also be thought of as a risk-management strategy as every type of equity has a distinct return and risk characteristics as well as different systemic risks, which describes how they respond to the market at large. Macroaxis enables investors to optimize portfolios that have a mix of equities (such as stocks, funds, or ETFs) and cryptocurrencies (such as Bitcoin, Ethereum or Monero)
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Note that this page's information should be used as a complementary analysis to find the right mix of equity instruments to add to your existing portfolios or create a brand new portfolio. You can also try the Watchlist Optimization module to optimize watchlists to build efficient portfolios or rebalance existing positions based on the mean-variance optimization algorithm.

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